Headline

Associate Consultant | Linux & UNIX Systems Expert | Cloud & Virtual Infra (Azure, VMware) | Automation with Ansible | RHEL Specialist | ML Engineer | Intern’d at Samsung R&D | Data Science Enthusiast

About

From Code to Cloud: My Journey as a Systems Architect in the Making Tech is more than just a profession to me—it's a playground where I build, break, and optimize. I’m Nihit Kumar, an Associate Consultant at Capgemini with 3+ years of hands-on experience in Linux and UNIX system administration. I specialize in managing enterprise infrastructure across cloud (Azure), virtual (VMware), and physical environments, with a deep focus on automation, uptime, and scalability. What sets me apart? My ability to blend system administration with smart automation using Ansible and Python scripting. I’ve led multiple successful RHEL OS upgrades, reduced patching time with automated workflows, and optimized system performance for critical financial services infrastructure. Beyond operations, I’ve also dabbled in data science—building audio code-switching detection models at Samsung R&D and EDA frameworks at Tata Steel. I thrive in high-stakes environments where precision, uptime, and collaboration matter. Whether it’s provisioning a new server, writing a Bash script to automate routine tasks, or diagnosing complex infra issues—I bring energy, clarity, and solutions. Looking ahead, I’m excited about roles that let me deepen my DevOps knowledge, expand into cloud-native architecture, and drive infrastructure excellence at scale. Let’s connect—whether you’re building resilient infra, solving tough ops problems, or just love talking tech!

Location

Bengaluru

Work experience

Associate Consultant at Capgemini, Apr 2025 - Present · 1 yr 1 mo, Bengaluru, As an Infrastructure Administrator for a leading U.S. financial firm (as client), I manage mission-critical systems across physical, virtual, and cloud environments (Azure, VMware). I’ve streamlined Linux operations—from system installations and patch management to performance tuning and disaster recovery—boosting system uptime and stability. My key impact includes executing seamless OS upgrades from RHEL 7 to 9, managing over 100+ virtual and physical servers, and automating tasks using Ansible to cut patching time by 40%. I ensure robust security through proactive system hardening and backup protocols (Veritas NetBackup, VMware snapshots), contributing to zero downtime in critical scenarios. My role also involves RCA reporting and coordination with global vendors. My hands-on expertise spans LVM, disk partitioning, and performance monitoring using Datadog. This role has refined my troubleshooting capabilities and strengthened my ability to manage enterprise infrastructure end-to-end.

Senior Analyst at Capgemini, Jul 2022 - Mar 2025 · 2 yrs 9 mos, Bengaluru, Karnataka, India

Intern at Capgemini, Feb 2022 - Jul 2022 · 6 mos, Bengaluru, Karnataka, India

ML Research Intern at Samsung R&D Institute India, Jun 2021 - Jan 2022 · 8 mos, Bengaluru, At Samsung R&D, I was part of a 7-member team working on a cutting-edge code-switching detection project. I developed machine learning models to identify Hindi-English language transitions in audio using Python libraries like scikit-learn and librosa. I engineered and evaluated multiple models (KNN, Random Forest, CNN), achieving over 80% accuracy—a significant milestone for multilingual audio processing. This solution had potential for real-time transcription tools, contributing to Samsung’s innovation roadmap. I handled end-to-end data preprocessing, feature extraction, and model evaluation, all in a collaborative Agile environment. This internship sharpened my research thinking, deepened my ML knowledge, and emphasized the value of production-level prototyping in tech R&D.

Data Science Intern at Tata Steel, Dec 2020 - Jan 2021 · 2 mos, Jamshedpur, Jharkhand, India, During my internship at Tata Steel, I built a robust Generic Exploratory Data Analysis (G-EDA) framework to automate preprocessing tasks across diverse datasets. The framework included data cleaning, transformation, and visualization modules—reducing manual effort by 60% in preliminary analysis. It was deployed on live datasets used in predictive modeling, helping the data analytics team fast-track model readiness. Working under seasoned data scientists, I also contributed to shaping modular Python scripts for dynamic adaptability, increasing the framework’s usability across projects. This internship laid the foundation for my data science interest and gave me real-world exposure to business-centric ML workflows.

Education

Bachelor of Technology - BTech, Computer Science and IT, C. V. Raman Global University, Bhubaneswar

High School, Science with Computer, Tagore academy

Public links

github: https://github.com/nihitkr